Book Image

Python Digital Forensics Cookbook

By : Chapin Bryce, Preston Miller
Book Image

Python Digital Forensics Cookbook

By: Chapin Bryce, Preston Miller

Overview of this book

Technology plays an increasingly large role in our daily lives and shows no sign of stopping. Now, more than ever, it is paramount that an investigator develops programming expertise to deal with increasingly large datasets. By leveraging the Python recipes explored throughout this book, we make the complex simple, quickly extracting relevant information from large datasets. You will explore, develop, and deploy Python code and libraries to provide meaningful results that can be immediately applied to your investigations. Throughout the Python Digital Forensics Cookbook, recipes include topics such as working with forensic evidence containers, parsing mobile and desktop operating system artifacts, extracting embedded metadata from documents and executables, and identifying indicators of compromise. You will also learn to integrate scripts with Application Program Interfaces (APIs) such as VirusTotal and PassiveTotal, and tools such as Axiom, Cellebrite, and EnCase. By the end of the book, you will have a sound understanding of Python and how you can use it to process artifacts in your investigations.
Table of Contents (11 chapters)

Introduction

Technology has come a long way and, with it, the extent to which tools are made widely available has changed too. As a matter of fact, being cognizant of the tools' existence is half the battle due to the sheer volume of tools available on the internet. Some of these tools are publicly available and can be bent toward forensic purposes. In this chapter, we will learn how to interact with websites and identify malware through Python, including an automated review of potentially malicious domains, IP addresses, or files.

We start out by taking a look at how to manipulate Internet Evidence Finder (IEF) results and perform additional processing outside of the context of the application. We also explore using services such as VirusShare, PassiveTotal, and VirusTotal to create HashSets of known malware, query suspicious domain resolutions, and identify known bad domains...